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PHASE 2 - SOLVE PROBLEMS BY APPLYING THE ALGORITHMS OF THE UNIT 1 Activity

SANDRA MILENA CASTELLAR FERNANDA YUBELY GOMEZ VIANNY KATHERINE GUZMAN Student

PAULA ANDREA CARVAJAL Tutor

TEORIA DE LAS DECISIONES 212066_30 Course

UNIVERSIDAD NACIONAL ABIERTA Y A DISTANCIA (UNAD) Marzo - 2018

INTRODUCTION The present document aims to document the reader, in the corresponding to the algorithms of unit 1, the course theory of decisions, thus achieving that it achieves, differentiate said algorithms, to make decisions and process optimization. We present exercises of great application, exercises are part of the industrial engineer's work performance, allowing then to achieve, tools to develop, perfectly as future professionals. The presented algorithms solve important questions for companies, for example, it solves questions such as, Is it better to manufacture or subcontract? When it is better for me to buy or produce a product, therefore we consider important the dynamics and information provided by the course. It presents a collaborative work, with ideals, with several perspectives that broaden concepts and help to better understand the subject.

Problem 1. DECISION TREES, EVPI and EVMI Teratex, a textile company that has a productive experience in the foreign market of 25 years, must decide if it manufactures a new product in its main plant, or if on the contrary the purchase from an external supplier. The profits depend on the demand of the product. The table shows projected profits, in millions of dollars. Table 1. Decision process for the commercialization of the product States of nature Decision Demand lowDemand low Demand High alternative utility average - utility utility Manufacture Subcontract Buy Probabilities Ʃ = 1

235 213 223

273 229 235

307 267 276

0,28

0,32

0,4

PART 1. DECISION TREES, EVPI and EVMI According to the corresponding information in Table 1 and the Predicted Value of Perfect Information (EVPI) theory, the Expected Value of Sample Information (EVMI) and Decision Trees, respond: a. Use EVPI to determine if the company should try to get a better estimate of the demand.

A better estimation of the demand is recommended, since when applying VEIP, it results in zero, that is, they do not generate a profit. | | | |

b. A test market study of potential product demand is expected to report a favorable (F) or unfavorable (U) condition. The relevant conditional probabilities are: P(F/low) = 0,25

P(D/low) = 0,75

P(F/low average) = 0,31

P(D/ low average) = 0,69

P(F/high) = 0,5

P(D/high) = 0,5

c. What is the expected value of market research information? What is the efficiency of the information? In times and / or favorable conditions it is recommended to sub manufacture with a profit of 284,213 Million dollars; In unfavorable times it is also recommended to manufacture, and a profit of 271,13 Million dollars is expected. The efficiency of the information is 0%, so we interpret that if the results are set in motion the profit will not be relevant and also, the probabilities given in the problem should be verified.

Problem 2. DECISION TREES, EVPI and EVMI ElectroCom, a company that manufactures electronic components for the introduction in its product catalog, must decide whether to manufacture a new product in its main plant, subcontract it with company supervision or if it buys it from an external supplier. The profits depend on the demand of the product. The table shows projected profits, in millions of dollars. Table 2. Decision process for the commercialization of the product States of nature Demand Demand Decision Demand Demand low High alternative lowHigh average - Medium utility utility utility utility Manufacture 215 242 257 263 Subcontract 213 241 249 276 Buy 213 254 253 268 Lease 215 249 249 275 Outsource 214 246 253 276 Probabilities Ʃ = 0,22 0,19 0,29 0,3 1 PART 2. DECISION TREES, EVPI and EVMI According to the corresponding information in Table 2 and the Predicted Value of Perfect Information (EVPI) theory, the Expected Value of Sample Information (EVMI) and Decision Trees, respond: a. Use EVPI to determine if the company should try to get a better estimate of the demand.

b. A test market study of potential product demand is expected to report a favorable (F) or unfavorable (U) condition. The relevant conditional probabilities are: P(F/low) = 0,2

P(D/low) = 0,8

P(F/low average) = 0,2

P(D/ low average) = 0,8 P(D/ high medium) = P(F/high medium) = 0,35 0,65 P(F/high) = 0,5

P(D/high) = 0,5

c. What is the expected value of market research information? In times and / or favorable conditions it is recommended to sub Outsources with a profit of 467,81 Million dollars; In unfavorable times it is also recommended to Outsources, and a profit of 246,28 Million dollars is expected. d. What is the efficiency of the information? We have an efficiency of 100%, since VEM equals VEIP, therefore the expected values in favorable and unfavorable weather will be accurate

Problem 3. DECISION TREES, EVPI and EVMI Teratextyl, a textile company that has a productive experience in the foreign market of 30 years, must decide if it manufactures a new product in its main plant, or if on the contrary the purchase from an external supplier. The profits depend on the demand of the product. The table shows projected profits, in millions of dollars. Table 3. Decision process for the commercialization of the product States of nature Demand Demand Decision Demand Demand low High alternative lowHigh average Medium utility utility - utility utility Manufacture 313 352 350 375 Subcontract 313 353 352 375 Buy 314 338 345 373 Lease 315 335 349 369 Outsource 319 346 356 375 Probabilities Ʃ = 1 0.25 0.25 0.30 0.20 PART 3. DECISION TREES, EVPI and EVMI According to the corresponding information in Table 3 and the Predicted Value of Perfect Information (EVPI) theory, the Expected Value of Sample Information (EVMI) and Decision Trees, respond: a. Use EVPI to determine if the company should try to get a better estimate of the demand.

b. A test market study of potential product demand is expected to report a favorable (F) or unfavorable (U) condition. The relevant conditional probabilities are: P(F/low) = 0,22

P(D/low) = 0,78

P(F/low average) = 0,35

P(D/ low average) = 0,65 P(D/ high medium) = P(F/high medium) = 0,33 0,67 P(F/high) = 0,42

P(D/high) = 0,58

c. What is the expected value of market research information? What is the efficiency of the information? In times and / or favorable conditions it is recommended to sub Outsources with a prJofit of 474,39 Million dollars; In unfavorable times it is also recommended to Outsources, and a profit of 346,1616 Million dollars is expected. We have an efficiency of 100%, since VEM equals VEIP, therefore the expected values in favorable and unfavorable weather will be accurate

SCREEN SHOTS SOLUTION EXERCISES WITH THE WINQSB Problem 1

CONCLUSIONS The decision theory opens the way to find out what the best option when deciding on an important event give our financial or business life. The development of this activity allows us to apply the theoretical knowledge concerning the theory of decisions, by solving the applicative problems exposed during the activity. when developing the problems that bring the practice in excel, we understand that although there are obvious figures, we have to check if it is true and convenient to invest in something that will improve our future.

REFERENCES BIBLIOGRAPHICS 

Sanderson, C. (2006). Analytical Models for Decision Making. New York, USA: McGraw-Hill Education Editorial. Retrieved from http://bibliotecavirtual.unad.edu.co:2051/login.aspx?direct=true&db=nleb k&AN=234098&lang=es&site=eds-live

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Gilboa, I. (2001). A Theory of Case-Based Decisions. Camdridge, UK: Cambridge University Press Editorial. Retrieved from http://bibliotecavirtual.unad.edu.co:2051/login.aspx?direct=true&db=nleb k&AN=72982&lang=es&site=eds-live

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Rokach, L. (2008). Data Mining With Decision Trees: Theory And Applications, Bern, Switzerland: H. Bunke, University Bern, Switzerland. Retrieved from http://bibliotecavirtual.unad.edu.co:2051/login.aspx?direct=true&db=nleb k&AN=236037&lang=es&site=eds-live